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<caption align="top"> Dictionary performance on ground truth set (n=400) </caption>
<tr> <th>  </th> <th> Policy/Policies </th> <th> Dict 1 </th> <th> Dict 2 </th> <th> Dict 3 </th>  </tr>
  <tr> <td align="right"> F1 Avg </td> <td align="right"> 0.77 </td> <td align="right"> 0.85 </td> <td align="right"> 0.9 </td> <td align="right"> 0.92 </td> </tr>
  <tr> <td align="right"> Precision Avg </td> <td align="right"> 0.88 </td> <td align="right"> 0.91 </td> <td align="right"> 0.92 </td> <td align="right"> 0.92 </td> </tr>
  <tr> <td align="right"> Recall Avg </td> <td align="right"> 0.74 </td> <td align="right"> 0.82 </td> <td align="right"> 0.89 </td> <td align="right"> 0.93 </td> </tr>
  <tr> <td align="right"> F1 = 0 </td> <td align="right"> 0.9 </td> <td align="right"> 0.92 </td> <td align="right"> 0.95 </td> <td align="right"> 0.95 </td> </tr>
  <tr> <td align="right"> F1 = 1 </td> <td align="right"> 0.64 </td> <td align="right"> 0.77 </td> <td align="right"> 0.86 </td> <td align="right"> 0.89 </td> </tr>
  <tr> <td align="right"> Krippendorff's Alpha </td> <td align="right"> 0.54 </td> <td align="right"> 0.69 </td> <td align="right"> 0.81 </td> <td align="right"> 0.84 </td> </tr>
  <tr> <td align="right"> True Positives </td> <td align="right">  58 </td> <td align="right">  77 </td> <td align="right">  95 </td> <td align="right"> 107 </td> </tr>
  <tr> <td align="right"> True Negatives </td> <td align="right"> 278 </td> <td align="right"> 277 </td> <td align="right"> 274 </td> <td align="right"> 266 </td> </tr>
  <tr> <td align="right"> False Positives </td> <td align="right">   4 </td> <td align="right">   5 </td> <td align="right">   8 </td> <td align="right">  16 </td> </tr>
  <tr> <td align="right"> False Negatives </td> <td align="right">  60 </td> <td align="right">  41 </td> <td align="right">  23 </td> <td align="right">  11 </td> </tr>
   </table>
